Analyzing Time Series Data for Parkinson’s Wearables: Alumni Spotlight on Jordan Webster

At The Data Incubator we run a free eight-week data science fellowship to help our Fellows land industry jobs. We love Fellows with diverse academic backgrounds that go beyond what companies traditionally think of when hiring data scientists. Jordan was a Fellow in our Spring 2017 cohort who landed a job with one of our hiring partners, IronNet Cybersecurity.

Tell us about your background. How did it set you up to be a great data scientist?

My background is in particle physics. As a physicist, I analyzed large datasets of particle collision images, and I used machine learning tools to classify rare and interesting collisions.

What do you think you got out of The Data Incubator?

At The Data Incubator I I learned a whole new toolset for approaching data analytics. I was exposed to new concepts like language processing and map-reduce, which never arose in physics. Furthermore, I was coached on how to best market myself to employers.

What advice would you give to someone who is applying for The Data Incubator, particularly someone with your background?

The Data Incubator is not just about writing code and doing statistical analysis. It’s also an opportunity to narrow your focus and zero in on a particular industry that you find interesting. To those applying, I recommend taking some time to think about why you are interested in data science, and where you want to end up down the road.

What’s your favorite thing you learned while at The Data Incubator? This can be a technology, concept, or whatever you want!

I learned that the skills we develop in scientific Ph.D. programs are incredibly marketable and useful to a very eclectic mix of companies.

Describe your Data Incubator Capstone Project

For my capstone project, I worked with a small tech startup that develops wearable devices (like Fitbits) for people with Parkinson’s Disease. The goal of my project was to analyze time series data from these devices and build a model that could be used to diagnose Parkinson’s Disease.

How did you come up with the idea for the project?

I was lucky to have been selected for a company-sponsored project. This means I didn’t need to go through the trouble of coming up with my own amazing topic and finding a good dataset.

What technologies did you use and what skills did you learn at TDI that you applied to the project?

I applied a lot of time series analysis tools that I had never used in particle physics.

What was your most surprising or interesting finding?

I found that Parkinson’s patients can be identified by looking for high-frequency acceleration modes in peoples’ arms and legs.

Describe the business application for this project (how could a company use your work or your data)

The startup that I worked with is using the tools I developed to get funding from their investors. Eventually, my project will serve as a base for their IP.

Where are you going to be working and tell us a little about your new job!

I will be working at a Cybersecurity startup in the DC area called IronNet. I will develop analytical tools and unsupervised models for detecting suspicious network traffic on large-company servers.